golosovRST

Overview

golosovRST is an R package for Golosov Relative Size Triangle (RST) classification and plotting.
It computes RST coordinates, classifies party-system observations into Golosov subtypes using polygon mapping, and produces publication-ready RST plots.

Contents

• .validate_rst_input()
• plot_rst()
• rst_classify()
• rst_coords()

Package metadata

• Type: Package
• Title: Golosov Relative Size Triangle Classification and Plotting
• Version: 0.0.1
• License: MIT + file LICENSE
• Encoding: UTF-8
• Imports: ggplot2, rlang
• Suggests: sf, testthat (>= 3.0.0), dplyr
• NeedsCompilation: no
• Author/Maintainer: Federico Taddei (federico.taddei@unimi.it)
• Repository: CRAN
• Date/Publication: 2026-09-03 11:50:37 UTC

Installation

install.packages("golosovRST")

Functions

.validate_rst_input(data)

Validate input for Golosov RST functions.

plot_rst(data, label_col = NULL)

Plot Golosov Relative Size Triangle.

Arguments

• data: A data.frame containing numeric columns s1, s2, s3, representing the seat shares of the three largest parties in parliament after the election.
• label_col: Optional character scalar: name of a column used as point labels.

Value

• A ggplot2 object.

rst_classify(data, offset = 5e-16)

Classify observations in Golosov subtypes using RST polygons.

Arguments

• data: A data.frame containing numeric columns s1, s2, s3, representing the seat shares of the three largest parties in parliament after the election.
• offset: Small numeric offset used to avoid polygon-edge ambiguity.

Value

• A data.frame with coordinates and golosov_subtype.

rst_coords(data)

Compute Golosov relative size coordinates.

Arguments

• data: A data.frame containing numeric columns s1, s2, s3, representing the seat shares of the three largest parties in parliament after the election.

Value

• A data.frame with original columns plus sr, x, and y.

Example

library(golosovRST)

mydata <- data.frame(
  country = c("uk 2015", "ita 2013", "spa 2015"),
  s1 = c(0.508, 0.4714, 0.3514),
  s2 = c(0.357, 0.1730, 0.2571),
  s3 = c(0.086, 0.1556, 0.1971)
)

plot_rst(mydata, label_col = "country")
cls <- rst_classify(mydata)
crd <- rst_coords(mydata)

cls
crd

Example plot

Example output: rst_classify(mydata)

cls

   country     s1     s2     s3     sr       golosov_subtype         X         Y
1  uk 2015 0.5080 0.3570 0.0860 0.0490  Two-Party Monovalent 0.7289048 0.2423698
2 ita 2013 0.4714 0.1730 0.1556 0.2000 Multiparty Monovalent 0.5555556 0.5296396
3 spa 2015 0.3514 0.2571 0.1971 0.1944 Multiparty Monovalent 0.8272261 0.7172957

Example output: rst_coords(mydata)

crd

   country     s1     s2     s3     sr         x         y
1  uk 2015 0.5080 0.3570 0.0860 0.0490 0.7289048 0.2423698
2 ita 2013 0.4714 0.1730 0.1556 0.2000 0.5555556 0.5296396
3 spa 2015 0.3514 0.2571 0.1971 0.1944 0.8272261 0.7172957

References

• Golosov, G. V. (2011). Party system classification: A methodological inquiry. Party Politics, 17(5), 539–560. https://doi.org/10.1177/1354068810377189
• Golosov, G. V. (2014). Towards a classification of the world's democratic party systems, step 2: Placing the units into categories. Party Politics, 20(1), 3–15.

Documentation

• CRAN package page: https://CRAN.R-project.org/package=golosovRST
• Full reference manual (HTML): https://cran.r-project.org/web/packages/golosovRST/refman/golosovRST.html
• Reference manual (PDF): https://cran.r-project.org/web/packages/golosovRST/golosovRST.pdf

DOI

https://doi.org/10.32614/CRAN.package.golosovRST